1649

Accidental experiments: ecological and evolutionary insights and opportunities derived from global change

Janneke HilleRisLambers , Ailene K. Ettinger , Kevin R. Ford , David C. Haak , Micah Horwith , Brooks E. Miner , Haldre S. Rogers , Kimberly S. Sheldon , Joshua J. Tewksbury , Susan M. Waters and Sylvia Yang

J. HilleRisLambers (jhrl@u.washington.edu), A. K. Ettinger, K. R. Ford, D. C. Haak, M. Horwith, B. E. Miner, H. S. Rogers, K. S. Sheldon, J. J. Tewksbury, S. M. Waters and S. Yang, Dept of Biology, Univ. of Washington, Seattle, WA 98195-1800, USA. DCH also at: Dept of Biology, Indiana Univ., Bloomington, IN 47405, USA. BEM also at: Dept of Ecology and Evolutionary Biology, Cornell Univ., Ithaca, NY 14853, USA. HSR also at: Dept of Ecology and Evolutionary Biology, Rice Univ., Houston, TX 77098, USA. KSS also at: Dept of Biology, Univ. of Utah, Salt Lake City, UT 84112, USA. JJT also at: Luc Hoff mann Inst., WWF International, Avenue du Mont-Blanc 27, CH-1196 Gland, Switzerland. SY also at: Western Washington Univ., Shannon Point Marine Center, 1900 Shannon Point Road, Anacortes, WA 98225, USA.

Humans are the dominant ecological and evolutionary force on the planet today, transforming habitats, polluting environ-ments, changing climates, introducing new species, and causing other species to decline in number or go extinct. Th ese worrying anthropogenic impacts, collectively termed global change, are often viewed as a confounding factor to minimize in basic studies and a problem to resolve or quantify in applied studies. However, these ‘ accidental experiments ’ also represent opportunities to gain fundamental insight into ecological and evolutionary processes, especially when they result in perturba-tions that are large or long in duration and diffi cult or unethical to impose experimentally. We demonstrate this by describing important fundamental insights already gained from studies which utilize global change factors as accidental experiments. In doing so, we highlight why accidental experiments are sometimes more likely to yield insights than traditional approaches. Next, we argue that emerging environmental problems can provide even more opportunities for scientifi c discovery in the future, and provide both examples and guidelines for moving forward. We recommend 1) a greater fl ow of information between basic and applied subfi elds of ecology and evolution to identify emerging opportunities; 2) considering the advan-tages of the ‘ accidental experiment ’ approach relative to more traditional approaches; and 3) planning for the challenges inher-ent to uncontrolled accidental experiments. We emphasize that we do not view the accidental experiments provided by global change as replacements for scientifi c studies quantifying the magnitude of anthropogenic impacts or outlining strategies for mitigating impacts. Instead, we believe that accidental experiments are uniquely situated to provide insights into evolutionary and ecological processes that ultimately allow us to better predict and manage change on our human-dominated planet.

Humans are the dominant ecological and evolutionary force on our planet, with our activities altering populations, com-munities and ecosystems on a global scale (Vitousek et al. 1997, Palumbi 2001). For example, human-induced habitat loss and fragmentation impact virtually all terrestrial habi-tats (Sala et al. 2000, Hoekstra et al. 2005). Advances in agriculture, medicine, energy and industry have resulted in widespread changes to existing biogeochemical cycles (e.g. nitrogen, phosphorus, carbon dioxide) as well as the introduction of novel chemicals to the environment (e.g.

agrochemicals, CFC’s, antibiotics: Tilman et al. 2001, Smith et al. 2006, Martinez 2009). Anthropogenic alterations of the carbon cycle have already resulted in global climate change, with even greater change expected in the future (IPCC, Climate Change Synthesis Report 2007). Th e glo-balization of trade has led to an enormous reshuffl ing of biotas and a rapid rise in invasive species (Levine and D’Antonio 2003). All of these activities, coupled with increased harvesting of species for food or natural resources, intensifi ed illegal hunting, and protection of human assets

Oikos 122: 1649–1661, 2013

doi: 10.1111/j.1600-0706.2013.00698.x

© 2013 Th e Authors. Oikos © 2013 Nordic Society Oikos

Subject Editor: Dustin Marshall. Accepted 19 June 2013CC h o i c e

E d i t o r ’s

OIKOS

Humans have an increasingly large impact on the planet. In response, ecologists and evolutionary biologists are dedicating increasing scientifi c attention to global change, largely with studies documenting biological effects and testing strategies to avoid or reverse negative impacts. In this article, we analyze global change from a differ-ent perspective, and suggest that human impacts on the environment also serve as valuable ‘accidental experi-ments’ that can provide fundamental scientifi c insight. We highlight and synthesize examples of studies taking this approach, and give guidance for gaining future insights from these unfortunate ‘accidental experiments’.

Synt

hesi

s

1650

are dramatically infl uencing the diversity and structure of ecosystems around the world (Reid et al. 2005).

Th e magnitude of environmental problems faced by humanity has not escaped the attention of the scientifi c community, with many studies documenting the impacts of global change on individual species or ecosystems (Fig. 1A – B, Edmondson 1970, Vitousek and Walker 1989, Laurance et al. 2002, Parmesan and Yohe 2003, Ripple and Beschta 2006). Global change has even resulted in the development of entirely new ecological and evolutionary subdisciplines and journals (e.g. Conservation Genetics, Restoration Ecology). Traditionally, a dichotomy existed between these ‘ applied ’ research directions and more fun-damental studies, with anthropogenic global change often viewed as a problem to quantify or resolve in the former or as a confounding factor to minimize in the latter. Despite the increased attention on global change factors in both ecological and evolutionary fi elds (Fig. 1A – B), we believe

this dichotomy still exists to some extent, as refl ected by the lack of cross-citations between traditionally ‘ basic ’ ecological and evolutionary journals and those ‘ applied ’ journals addressing the biological impacts of global change (Fig. 1C).

We argue that fundamental insights into ecological and evolutionary processes can be gained by considering global change factors as ‘ accidental experiments ’ , much as Diamond argued that ‘ natural experiments ’ are an important comple-ment to lab and fi eld experiments (1983). Scientists going back to Darwin, who used naturalized species to suggest competition is most severe between close relatives (1859), and Grinnell, who proposed that the introduced English sparrow be used to investigate ecotypic adaptation (1919), have made similar suggestions for specifi c case studies. More recently, Sax et al. made a parallel argument for introduced species (2007). In this paper, we expand on these argu-ments by providing a retrospective view on ecological and

Ecology(Ecological Monographs,Ecology, Ecology Letters,Journal of Ecology, Oikos,

Oecologia)

Evolution(BMC Evolutionary Biology,

Evolution, Journal ofEvolutionary Biology

Conservation(Biodiversity and Conservation,

Biological Conservation, BiologicalInvasions, Conservation Biology,

Conservation Genetics, EnvironmentalConservation or Ecological

Applications)

14.06%

7.62%

16.9

1%

22.6

5%2.45%

5.74%

1990 1995 2000 2005 2010

Pro

porti

on S

tudi

es

Habitat changePollutionClimate ChangeInvasive speciesSpecies decline& loss

(C) Information Flow

(A) Ecological Journals (B) Evolutionary Journals

1990 1995 2000 2005 2010YearYear

0.15

0.10

0.05

0.00

0.15

0.10

0.05

0.00

Figure 1. Citation history of global change terms in the last 23 years (A, B), showing an increasing interest by the scientifi c community that appears greater in ecological (A) than evolutionary (B) fi elds. Plotted is the proportion of studies (of all published in select ecological and evolutionary journals that year) including specifi c keywords in the title, abstract or keyword list that relate to the fi ve global change factors. Th e fl ow of information (according to number of citations) between ‘ basic ’ and ‘ applied ’ journals may explain these diff erences (C); it is greater in the fi eld of ecology than the fi eld of evolution. Th e size of each arrow and percentage indicates the proportion of articles (published between 2008 – 2013 in select journals) in one subdiscipline (that the arrow is pointing to) that cite at least one article published in journals in the other subdiscipline in 2008 (that the arrow is pointing from). More details on Web of Science search parameters used to generate these fi gures are in Supplementary material Appendix A1 (for Fig. 1A – B) and Supplementary material Appendix A2 (for Fig. 1C).

1651

evolutionary insights gained by all global change factors, and a prospective view by outlining a path to maximize continued insight. Specifi cally, we fi rst summarize important ecological and evolutionary insights that fi ve broad global change fac-tors have already provided (e.g. Box 1), and discuss when such insights are uniquely gained from accidental experiments (as opposed to more traditional observational studies or manip-ulative experiments). Next, we argue that accidental experi-ments created by ongoing or emerging global change factors will yield additional ecological and evolutionary insights in the future, and we provide suggestions on how both to identify such opportunities and design scientifi c studies that maximize insight from these opportunities.

A retrospective view: insights already gained from the study of global change factors

Habitat transformation

Nearly a fi fth of the worlds ’ land surface has been converted to human use (Hoekstra et al. 2005). Th ese habitat transfor-

mations cause a wide variety of changes to the environment that can be viewed as ‘ treatments ’ (Table 1). For example, deforestation, urbanization and agriculture have reduced the amount of habitat available for most species, as well as increased habitat fragmentation and disturbance rates. Th us, the direct eff ects of habitat transformation provide biologists with the opportunity to investigate the impacts of habitat size and quality, habitat isolation, and the eff ects of edges and disturbances on gene fl ow, populations, species, commu-nities and ecosystems (Fukami and Wardle 2005, Laurance 2008). Th rough these direct eff ects, habitat transformation can dramatically increase local extinction rates, providing biologists with additional opportunities to examine, for example, how changes in biotic components of communities infl uence community and ecosystem structure (Table 1).

Evolutionary biologists and ecologists have already gained tremendous insight into population, community and ecosystem-level processes by studying these ‘ treatments. ’ For example, fragmented habitats are frequently used to establish that small population sizes and isolation generally negatively infl uence gene fl ow and increase inbreeding depression

Box 1. Examples of key ecological and evolutionary insights from the study of fi ve global change factors, including studies on habitat trans-formation (Galetti et al. 2013), pollution (Vonlanthen et al. 2012), climate change (Harsch et al. 2009), introduced species (Rogers et al. 2012), and the recovery of a species from low population numbers (Duckworth and Badyaev 2007).

Global change factor Example ecological/evolutionary insightHabitat transformation: deforestation and defaunation in Brazil hasled to the local extinction of large-gaped seed dispersers like the channel-billed toucan1. Galetti et al. (2013) studied palm populationsin these forests and found a reduction in their seed size in fragmentswithout these large-gaped seed dispersers, consistent with alteredselective pressures on seed size with disperser loss.

Pollution: eutrophication of Swiss lakes2 leads to hypoxia, eliminatingspawning habitat for deep-dwelling whitefish. Vonlanthen et al. (2012)demonstrated that this decline in reproductive isolation relaxeddivergent selection between deep- and shallow-dwelling whitefish,and increased gene flow between previously distinct types, leadingto a loss of diversity (termed ‘reverse speciation’).

Climate change: most of the globe has warmed in the last 50–100years. Using a meta-analysis, Harsch et al. (2009) examined therelationship between warming and the position of treelines3 globally,demonstrating the importance of climate as well as other factors forthe establishment of this ecotone.

Introduced species: The introduction of the non-native brown treesnake to Guam has resulted in the functional extirpation of the nativeavifauna. Rogers et al. (2012) used this extinction to demonstratethat birds have strong top–down effects on spider abundances4

when they found 40× greater spider densities on Guam than onneighboring islands with intact avifauna.

Extinction/population decline: western bluebirds5 are recolonizingtheir historic range after rebounding from low populations (due tohabitat loss). Using this range expansion, Duckworth and Badyaev(2007) demonstrated that aggressive behavior is coupled withdispersal in expanding populations of this species, facilitating thedisplacement of mountain bluebirds by western bluebirds.

1 The channel-billed toucan Ramphastos vitellinus is capable of eating and dispersing large palm seeds. Picture courtesy of Guto Balieiro. 2 The River Rhone entering Lake Geneva, one of the lakes studied by Vonlanthen et al. Rama / Wikimedia Commons / CC-BY-SA-2.0-FR 3 Nothofagus treeline in Takahe Valley, Murchinson Mountains, New Zealand. Picture courtesy of Melanie Harsch. 4 Spider webs on Guam. Picture courtesy of Isaac Chellman. 5 A western bluebird Sialia mexicana . Picture courtesy of Alexander Badyaev.

1652

Table 1. Treatments resulting from global change factors, the evolutionary and ecological processes altered by these unintentional ‘ treat-ments ’ , and example insights that would have been diffi cult to achieve with more traditional experimental or observational approaches.

Global change factor Potential ‘ treatments ’

Evolutionary/ecological processes affected Example insights 3

Habitat transformationLess habitat areaMore isolated habitatsLess connectivityAltered habitat quality

Lower dispersal and gene fl ow 1 Altered population sizes 1 Loss of species and genetic diversity 2 Loss of biotic interactors 2

Studies supporting and refuting elements of theories of island biogeography and meta-population ecology are largely provided by fragmented habitats (Hanski 1998, Laurance 2008).

Altered competitive hierarchies 2 Altered selective regimes 2

PollutionIncreased resourcesToxins (poisons)Endocrine disruptorsAntibiotics

Greater productivity 1 Altered population sizes 1 Altered sex ratios 1 Increased mutation rates 1

The concept of alternative stable states, although long recognized as a theoretical possibility (May 1977), fi rst gained empirical support from studies of eutrophied lakes (Scheffer et al. 1993).

Radioactive materials Loss of species and genetic diversity 2 Loss of biotic interactors 2 Altered competitive hierarchies 2 Altered selective regimes 2

Climate changeWarmer temperaturesAltered precipitation regimesGreater variability in climateSea-level rise

Altered distributions (range shifts) 1 Altered phenological timing 1 Loss and gain of biotic interactors 2 Altered competitive hierarchies 2

Range limits are a classic ecological topic (Darwin 1859, MacArthur 1972). Studies documenting range shifts consistent with recent warming (Chen et al. 2011) support climatic controls over range limits.

Ocean acidifi cation Altered selective regimes 2 Loss/gain of habitats Succession 2

Introduced speciesSmall populationsLower/higher genetic diversityLoss of interactionsNovel interactions

Small population sizes 1 Founder effects 1 Inbreeding depression 1 Hybridization (heterosis) 1 Loss and gain of biotic interactors 1

Recognition that rapid evolutionary change in ecologically relevant traits (e.g. food acquisition traits, defense against predation or herbivory) can occur over short time scales was fostered by studies of introduced species (Carroll et al. 2007).

Range expansions 1 Adaptive radiation 2 Altered competitive hierarchies 2 Altered selective regimes 2

Species loss and declineSmall populationsLoss of interactionsGain of interactions

Greater demographic stochasticity 1 Loss of species and genetic diversity 1 Altered competitive hierarchies 2

Top–down control of ecosystems by apex predators is convincingly demonstrated by anthropogenic extinctions (Estes et al. 2011).

Altered selective regimes 2

1 Direct responses to global change factors. 2 Indirect responses to global change factors that have themselves been used to gain fundamental insight. 3 Several of these insights are not unique to the global change factor in question – for example, rapid evolutionary changes have been docu-mented in introduced species as well as species responding to climate change.

(Madsen et al. 1996, Westemeier et al. 1998, Saccheri et al. 1998, Morgan 1999, Buza et al. 2000, Templeton et al. 2001, Jump and Penuelas 2006). One recent study illustrates that selective pressures may also be altered in transformed habitats by documenting reduced seed size of palms in forest fragments where their large-gaped seed dispersers have become locally extinct (Box 1, Galetti et al. 2013). Many aspects of the theories of island biogeography and metapopulation dynamics (e.g. relationships between habitat size and diversity, habitat size and extinction, habi-tat isolation and colonization) have largely been clarifi ed by the characteristics of populations occurring in habitats reduced and fragmented through anthropogenic distur-bances (Bierregaard et al. 1992, Hanski and Ovaskainen 2000, Ricketts et al. 2001, Laurance et al. 2002). Th ese studies have illustrated that responses are often species and population specifi c, with generalizations possible based

on functional traits (e.g. average movement, body size). Another classic ecological topic – succession – has largely been explored in studies examining the response of popu-lations, species, communities and biogeochemical cycling to areas varying in time since agriculture or other human activities (Bard 1952, Bazzaz 1968, Gleeson and Tilman 1990, De Deyn et al. 2003, Goulden et al. 2011). Com-munity and ecosystem responses to habitat transformation have also generated fundamental insights. For example, eco-logical studies on coff ee plantations suggest a link between diversity and ecosystem functioning (Philpott et al. 2008), islands created by a dam in Venezuela helped address a clas-sic ecological question “Why is the world green?” (Hairston et al. 1960, Terborgh et al. 2001), and the creation of the Panama Canal allowed for a test of the importance of disper-sal versus competition in large-scale biogeographic patt erns of diversity (Smith et al. 2004).

1653

of alternative stable states was also strongly infl uenced by the study of eutrophication in lakes, when scientists noticed that small changes in an external driver (in this case, nutri-ents) could result in large changes in ecosystems (clear ver-sus turbid water) that could not be reversed without large decreases in the same external driver (Scheff er et al. 1993, Carpenter and Brock 2006).

Climate change Atmospheric carbon dioxide and methane levels are higher now than at any other time in the last 650 000 years, and will continue to rise (IPCC, Climate Change Synthesis Report 2007). Climate change resulting from these gases is expected to increase surface temperatures, alter precipitation regimes, and cause ocean warming and acidifi cation at unprecedented rates (IPCC, Climate Change Synthesis Report 2007). All of these abiotic factors are likely to directly infl uence the genetic make-up, physiology and abundance of organisms, and thus, the diversity of communities (Table 1). Indirect eff ects are also possible – for example, global warming has already increased glacial melting, which can create new, pre-viously uncolonized habitat where succession can proceed (Cannone et al. 2008). In addition, altered biotic interac-tions can result from climate-induced species range shifts, declines, and extinctions, including expansions of infectious diseases or pathogens (Harvell et al. 2002), phenological mis-matches (Harrington et al. 1999), and novel or ‘ no-analog ’ climates (Williams and Jackson 2007).

Despite the challenges of attributing biological responses to the long-term impacts of climate change, this global change factor has already resulted in many ecological and evolutionary insights. For example, warming has caused rapid genetic changes in populations, providing insights into the potential speed of evolutionary changes in response to environmental changes (Bradshaw and Holzapfel 2001, Reale et al. 2003, Balanya et al. 2006). Th ere are also many studies documenting shifts in species distributions and phe-nology in response to recent warming (reviewed by Parme-san and Yohe 2003, Parmesan 2006, Chen et al. 2011). Th is implies a fundamental role for climatic factors in determin-ing range limits (Crozier 2004, Beckage et al. 2008, Lenoir et al. 2008, Moritz et al. 2008, Chen et al. 2009, Harsch et al. 2009, Tingley et al. 2012) and the timing of phenologi-cal events (Fitter and Fitter 2002, Cotton 2003, Kauserud et al. 2008, Miller-Rushing and Primack 2008, Altermatt 2010, Bartomeus et al. 2011). However, it is also clear that species are responding to climate change idiosyncratically, stimulating many recent studies on the importance of phe-nological timing for species interactions (Visser et al. 1998, Both and Visser 2001, Edwards and Richardson 2004, Winder and Schindler 2004, Post and Forchhammer 2008, Both et al. 2009, Th ackeray et al. 2010) as well as the role of species interactions or traits in slowing or facilitating range shifts (Box 1, Harsch et al. 2009, Harley 2011, Pateman et al. 2012). We have also learned that phenotypic plastic-ity can play a central role in modulating species responses to changes in their environment (Charmantier et al. 2008, Lane et al. 2012), and that the degree to which species can track environmental shifts may determine the long-term survival of a population or species during periods of rapid change (Willis et al. 2008).

Pollution Pollution caused by environmental toxins (e.g. antibiotics, PCB ’ s), anthropogenic nutrient sources (e.g. nitrogen and phosphorus) and environmental disasters (e.g. oil spills, nuclear disasters like Chernobyl and Fukushima) provide many unintended ‘ treatments ’ , both evolutionary and eco-logical (Table 1). For example, radioactive pollutants can increase mutation rates (generally lowering fi tness) and endocrine disrupters can alter sex-ratios (Stoker et al. 2003), potentially allowing physiological or behavioral ecologists to determine the infl uence of such ‘ treatments ’ on population dynamics and behavior. Pollutants that are plant resources (e.g. N and P) can alter competitive hierarchies, eliminating some species and genotypes from populations and com-munities while allowing others to become abundant. Th ese resources also infl uence productivity and nutrient cycling, allowing for a better understanding of ecosystem dynamics (Suding et al. 2005, Smith et al. 2006). Finally, the indirect eff ects of these treatments further allow ecologists to exam-ine the community- and ecosystem-level impacts of indi-vidual species (when lost or gained) and allow evolutionary biologists to study how environmental pressures alter selec-tion on certain traits (e.g. antibiotic resistance), as well as the spatial and temporal scales over which these traits are fi xed or eliminated (Martinez 2009).

Th e biological impacts of pollution have clearly changed the way scientists think about ecological and evolutionary processes. Kettlewell’s seminal study, for example, demon-strated that traits (such as a dark color) can sweep through a population after selective pressures are changed, with pol-lution altering the relative camoufl age benefi ts of peppered moth morphs on lichen-covered versus sooty trees (Kettlewell 1955). Th is example has been reproduced in virtually every introductory biological textbook (Rudge 2005). Many stud-ies since have used pollution gradients to investigate rates of evolution and the traits that confer fi tness under changing environmental conditions (Hairston et al. 2005, Antonovics 2006, Saccheri et al. 2008, Eranen et al. 2009, Brede et al. 2009). Aquatic eutrophication has also been used to dem-onstrate the importance of visual mate choice and ecological opportunity for sexual selection or reproductive isolation in cichlids, sticklebacks and whitefi sh (Box 1, Seehausen et al. 1997, Candolin et al. 2007, Engstrom-Ost and Mattila 2008, Vonlanthen et al. 2012). Additionally, a breakdown in the relationship between coloration and immune func-tion in barn swallows near Chernobyl allowed evolutionary biologists to speculate that the link between sexual selec-tion linked and secondary sexual characters weakens under extreme environmental stress (Camplani et al. 1999, M ø ller and Mousseau 2006).

For ecologists, Edmondson’s seminal study of Lake Washington and more recent studies of systems experienc-ing anthropogenic nutrient loading have provided insight into the relative importance of nitrogen and phosphorus in limiting terrestrial and aquatic productivity (Edmond-son 1970, Ryther and Dunstan 1971, Smith et al. 2006). Additionally, the importance of resource niches for species diversity and coexistence has been examined with studies documenting relationships between the deposition of nitro-gen and phosphorus and the loss of terrestrial plant diver-sity (Stevens et al. 2004, Wassen et al. 2005). Th e concept

1654

Torchin et al. 2003, Reinhart and Callaway 2004, Hawkes et al. 2006, Callaway et al. 2011). Introduced species have also been studied in the context of ecosystem engineers and trophic cascades, illustrating that the impacts of individual species on populations, communities and ecosystems can be enormous (Box 1, Vitousek and Walker 1989, D’Antonio and Vitousek 1992, O’Dowd et al. 2003, Kurle et al. 2008, Baiser et al. 2008, Kimbro et al. 2009, Rogers et al. 2012). Th ese studies have also convincingly demonstrated that spe-cies interactions are enormously complex (Stinson et al. 2006, Edgell et al. 2009, Green et al. 2011) and often depend on the evolutionary history of the interacting species (Parker et al. 2006, Strauss et al. 2006a, Desurmont et al. 2011).

Species decline and loss Anthropogenic activities remove species from a variety of ecosystems through local extirpation or global extinction. According to the International Union for Conservation of Nature (IUCN), 16 928 species are threatened (criti-cally endangered, endangered or vulnerable) and global extinction rates are currently 100 – 1000 times greater than background levels (Dirzo and Raven 2003, Vie et al. 2009). Th e decline or loss of each population and species allows ecologists and evolutionary biologists to address a variety of questions (Table 1), including the dynamics of small populations (demographic stochasticity, genetic drift, population bottlenecks) and the role individual spe-cies play in structuring communities and ecosystems. For example, removing a species can sever interspecifi c interac-tions (competition, predation, mutualism, etc.) and illu-minate the importance of these interactions for remaining species. If a species ’ removal results in a large change to its community or ecosystem, that species can be identi-fi ed as a strong ecological interactor (e.g. keystone spe-cies or ecosystem engineer). Recovering or reintroduced populations of previously decimated species can provide additional insights into population spread and dynamics, and the infl uence of individual species on community and ecosystem processes.

Loss of strong interactors, reduction in population density, and loss of genetic diversity represent accidental experiments that have already been used to gain insight into basic questions in community ecology, population biology, evolutionary genetics, and life history evolution. For example, species experiencing population declines due to overharvesting or active culling have been observed to evolve life history traits in response to these anthropo-genic impacts (Coltman et al. 2003, Olsen et al. 2009, Sasaki et al. 2009, Darimont et al. 2009). These small populations have also demonstrated Allee effects may be common (Courchamp and Macdonald 2001). Addi-tionally, the negative impacts of inbreeding depression and the loss of genetic variability on population fitness have been clarified by studies of rare species (Westemeier et al. 1998, Vila et al. 2003). Studies of declining popu-lations have allowed ecologists to identify controls over population dynamics, exploring, for example, the rela-tive importance of intrinsic versus extrinsic mechanisms, and the importance of biotic and abiotic controls over population fluctuations (Jackson et al. 2001, Olsen et al. 2004, Ims et al. 2008, Anderson et al. 2008). The loss

Introduced species Th e purposeful or unintended movement of organisms into novel habitats has many consequences that can be studied by ecologists and evolutionary biologists (Table 1). Introduced species are initially at small population sizes and often have reduced genetic variation relative to popu-lations in their native ranges, allowing the study of founder events, Allee eff ects, demographic stochasticity and genetic drift. Multiple introductions can bring together genotypes from very diff erent native regions in introduced regions, and can provide insight into the potential role of genetic reshuffl ing in the establishment of successful genotypes (Roman and Darling 2007). Th ose introduced species that establish and spread also represent excellent opportunities to understand the drivers and rates of range expansions (Hastings et al. 2005) and the potential importance of eco-system engineers and/or top predators (Fukami and Wardle 2005). As introduced species generally leave behind the competitors, natural enemies, consumers, pathogens, and predators with which they interact in their native ranges, the study of introduced species also allows us to study the importance of coevolution for species ’ interactions (Callaway and Maron 2006, Strauss et al. 2006b). Over longer time scales, introduced species off er biologists the chance to observe how species evolve in response to novel climates and interactors, and the loss of native interactors (Strauss et al. 2006b). In addition to studying the introduced species, the invaded community can also become the target of study – lending itself to research on the relationship between disturbance, diversity, invasibil-ity, the trophic and ecosystem level impacts of individual invaders on the habitats they invade, and the manner in which native species evolve in response to these novel interactors (Strauss et al. 2006b, Callaway and Maron 2006, Sax et al. 2007).

Th e insights gained from the study of introduced spe-cies have been diverse and far ranging (reviewed by Fukami and Wardle 2005, Strauss et al. 2006b, Callaway and Maron 2006, Sax et al. 2007). On the evolutionary side, multiple introductions of common non-native species have resulted in novel genotypes relative to their native state (Kolbe et al. 2004, Roman 2006, Facon et al. 2008), which in some cases, appear responsible for the overwhelming success of the invader (Lavergne and Molofsky 2007). Introduced species have also supported the idea that evolutionary change can occur extremely rapidly, both in the introduced species and the native species responding to their introduction (Phillips and Shine 2004, Carroll et al. 2005, Zangerl and Berenbaum 2005, Siemann et al. 2006, Phillips et al. 2006, Montesinos et al. 2012). Finally, introduced species have provided several examples of speciation dynamics mediated through repro-ductive isolation, ecological opportunity and/or hybridiza-tion (Bush 1969, Filchak et al. 2000, Hendry 2001, Salmon et al. 2005, Fitzpatrick and Shaff er 2007, Ward et al. 2012).

Ecologists have also gained insight from introduced spe-cies. Early applied ecological work on biological control was based on the assumption that host-specifi c natural enemies can strongly regulate population sizes (Murdoch et al. 1985), and more recent studies indeed suggest that the loss of natural enemies in the invaded range is sometimes, but not always, correlated with invasive success (Mitchell and Power 2003,

1655

hypothesis (e.g. the role of climate in setting range limits), can allow for the kind of generalization (Parmesan 2006, Harsch et al. 2009, Chen et al. 2011) that might otherwise be diffi cult to achieve without highly coordinated networks of scientists replicating the same set of experiments. Simi-larly, accidental experiments can validate whether fi ndings from smaller-scale manipulative experiments scale up (e.g. species loss when nutrient limitation is overcome – Stevens et al. 2004, Suding et al. 2005, Wassen et al. 2005). Finally, when accidental experiments result in treatments that are simply unethical to intentionally impose (e.g. the introduc-tion of thousands of species to environments with novel selection pressures, the extirpation of apex predators from large numbers of ecosystems), they can allow scientists to empirically validate hypotheses that otherwise might pri-marily have remained in the realm of theory (e.g. top – down control of ecosystems: Hairston et al. 1960, Estes et al. 2011, rapid evolution: Carroll et al. 2007).

Moving forward: can additional ecological and evolutionary insights be gained from anthropogenic change? Th e fi ve broad global change factors we describe have already provided critical insight on a diverse array of evolutionary and ecological topics (Box 1). Th e infl uence of humans on the planet is increasing (Sala et al. 2000, Tilman et al. 2001, IPCC Climate Change Synthesis Report 2007), and ecologists

(or reintroduction) of top predators has also convincingly demonstrated the importance of top – down control for communities and ecosystems (Leopold et al. 1947, Estes et al. 1998, Ripple et al. 2001, Myers et al. 2007, Johnson and VanDerWal 2009, reviewed by Estes et al. 2011). Finally, a recent study demonstrated a role for dispersal and behavioral aggression in the re-expansion of western bluebirds into their historic range as their populations rebounded from low numbers (Box 1, Duckworth and Badyaev 2007).

Summary How critical have studies of the impacts of global change been for fundamental insights into ecological and evolutionary topics (e.g. Box 1)? We suspect there are many insights uniquely gained by accidental experiments, includ-ing the existence of ‘ alternative stable states, ’ the rapidity with which evolutionary change can occur, and the role of apex predators in community structure and ecosystem function (Table 1). In our opinion, there are several fac-tors that contribute to the role of accidental experiments in scientifi c discovery. First, accidental experiments often result in treatments that are extreme in magnitude (e.g. the eutrophication of lakes) or cover large spatial and tempo-ral scales (e.g. climate change), often diffi cult or impos-sible to impose experimentally (Table 2). Th us, accidental experiments that are repeatedly used to examine a particular

Table 2. Advantages and disadvantages of ‘ Accidental experiments ’ compared to more traditional approaches for studying ecological and evolutionary processes.

Characteristic

Traditional approaches

Accidental experimentsObservational studies Manipulative experiments

Control over treatments/ perturbations (strength of inference)

Low (unobserved/unmeasured confounding variables)

High Intermediate ( ‘ treatments ’ covary with other factors and may themselves be responses to global change)

Magnitude of treatment Low (depends on spatial or temporal variability)

Can be high (if manipulations allow)

Often high (may vary over time)

Appropriate control( ‘ null ’ treatment)

Can be challenging (absent, or depends on an appropriate choice of spatial or temporal observations)

Easy to impose (in a well-designed experiment)

Can be challenging (imposed by scale of anthropogenic perturbation or ability to foresee anthropogenic change)

Spatial scale (of treatment) Can be large Generally small Can be large (sometimes uneven)Temporal scale (of treatment) Based on time span of

observationsGenerally short, applied in a step fashion (i.e. a pulse experiment)

Can be long-term (often already imposed), applied in a step or gradual fashion (i.e. a pulse or press experiment), sometimes uneven

Diffi culty of imposing treatments

Easy (no treatments as such) Often diffi cult Easy (treatment already imposed)

Relative cost (equipment, supplies, labor)

Low (only requires sampling) High (in addition to sampling, treatments have to be imposed and maintained)

Low (only requires sampling)

Main advantages Large spatio-temporal scale possible; can help quantify semi-equilibrial dynamics; inexpensive and logistically simple

Control over experimental treatments; strength of inference

Treatments often over large spatial and long temporal scales; access to ‘ treatments ’ that are otherwise inaccessible

Main disadvantages Covariates and magnitude of perturbations often makes inference weak

Chance of experimental ‘ failure ’ (treatment doesn ’ t work); small spatial and temporal scale of ‘ treatments ’ ; often expensive and challenging logistically

‘ Treatments ’ infrequently applied in isolation (compromising inference); desired experimental design diffi cult to impose

1656

transformation of perspective necessary to highlight the diverse research opportunities associated with global change. Others have made similar arguments based on the obser-vation that our globe is increasingly human-dominated (Hobbs et al. 2006, Marris 2009). Despite the many insights described here (e.g. Box 1), as well as papers advocating the use of global change factors to gain fundamental insights (Fukami and Wardle 2005, Strauss et al. 2006a, Sax et al. 2007), we believe that it may still not occur to many that ongoing global change factors can be used to test basic theory, perhaps because the negative impacts of these perturbations makes the study of applied solutions seem more immediate. For example, mountain top mining is a habitat disturbance that aff ects � 8000 km 2 of southern Appalachian forests and streams (Box 2). Most ecologists and evolutionary biologists are probably aware of the environmental destruction moun-taintop mining brings, and the concomitant need for resto-ration projects. Yet there are few studies, to our knowledge, utilizing the opportunity to gain insights into basic ecologi-cal questions by documenting the long-term community or

and evolutionary biologists will undoubtedly continue to focus on global change factors, perhaps at even higher rates (Fig. 1). But would explicitly considering emerging global change factors as accidental experiments make fundamental insights more likely in the future? Identifying all insights that could be gained is challenging (we suggest a few in Box 2), but studies that have already considered global change fac-tors as accidental experiments can provide direction (e.g. Box 1). Here we outline approaches allowing ecologists and evo-lutionary biologists to 1) identify emerging opportunities in global change; 2) determine whether the ‘ accidental experi-ment ’ approach is superior to more traditional approaches for gaining fundamental insight; and 3) overcome the likely chal-lenges associated with the ‘ accidental experiment ’ approach.

Increase awareness of opportunities for basic research associated with emerging or ongoing environmental problems More communication between the ‘ applied ’ and ‘ basic ’ subfi elds of ecology and evolution might help achieve the

Box 2. Potential ecological and/or evolutionary insights that might be gained from recent or upcoming impacts of habitat transformation (Bernhardt and Palmer 2011), pollution (Lubchenco et al. 2012), climate change (Perovich and Richter-Menge 2009), introduced species (Dorcas et al. 2012) and species extinctions or declines (Wake and Vredenburg 2008).

Global change factor Example ecological/evolutionary insight

Habitat transformation: mountain top mining1 results in large scaleremoval of vegetation. This disturbance could be used to investigate (forexample) evolutionary changes in life history traits of initially colonizingspecies and the interplay of species inter actions and the environmentduring community assembly.

Pollution: the explosion of the Deepwater Horizon drilling rig2 in 2010resulted in one of the largest oil spills ever recorded. This disturbancecould be used to investigate (for example) how the resulting oil spillaltered selection regimes for sea floor microbes and the dynamics ofsuccession in areas barren of sea life.

Climate change: warming in the Arctic will likely result in an ice freenorth passage by the year 20203. The elimination of this geographicbarrier will increase migration between the Pacific and Atlantic Oceansbiotas, altering community composition and competitive dynamics, andthus, evolutionary dynamics.

Introduced species: pythons have invaded the Everglades in Florida,resulting in many novel interactions4. This invasion could be used toexamine when/how behavioral responses to snake predation are selectedfor, and whether decreased herbivory by deer whose numbers havedeclined due to python predation influences ecosystem functioning.

Extinction / population decline: dramatic declines in amphibian diversityand abundance5 are occurring world-wide (due to the effects of anemerging pathogen). These declines could be used to investigate the ecological role of frogs in food webs, and the evolutionary responses ofprey to the loss of an important biotic interaction.

1 A NASA Landsat satellite image of a surface mine in Boone County, West Virginia. This picture is in the public domain. 2 The remnants of the Deepwater Horizon on 20 April 2010. This picture was taken by a USGS employee and is in the public domain. 3 A NASA satellite image of Arctic sea ice in 2005. This image is in the public domain. 4 A non-native Burmese python and an American alligator in the Florida Everglades National Park. This image was taken by Lori Overhofer (NPS employee) and is in the public domain. 5 A frog infected by Chytridiomycosis (photo taken by Forrest Brem). This picture was fi rst published in PLoS Biology (Gewin 2008), and is therefore under Creative Commons Attribution 2.5 license.

1657

and evolutionary questions that might not otherwise be pos-sible (Box 2). For example, the perturbations introduced by mountain top mining and global amphibian declines are rel-evant to ecological or evolutionary topics of great contem-porary interest including community assembly (Ackerly and Cornwell 2007, Cavender-Bares et al. 2009, HilleRisLam-bers et al. 2012) and the adaptive repercussions of altered species interactions for ecosystems (Whitham et al. 2006). Direct experimental approaches for these topics do exist at smaller scales (e.g. rapid evolution in response to predator – prey dynamics: Yoshida et al. 2003, experimental community assembly: Fukami et al. 2005), but the resources required to impose these experimental treatments at the spatial (and temporal) scale of most human-induced changes (e.g. climate change) are beyond the scope of most ecology and evolu-tionary biology funding sources. Finally, many experimental manipulations that could elucidate the ecological and evolu-tionary dynamics of our study systems or species are simply unethical (for example, the virtual elimination of frogs or the introduction of a new apex predator – Box 2).

Foresee and plan for the challenges inherent in studying accidental experiments Once a scientist decides a particular global change factor will be used to explore a particular ecological or evolutionary topic (i.e. an ‘ accidental experiment ’ is identifi ed), there are still important challenges to consider (Table 2). Most obvi-ously, the investigator has little to no control over where, when, or over what spatial extent global change factors are imposed, making many desirable aspects of experimental design impossible. It may therefore be diffi cult to obtain suffi cient replicates of the treatment and avoid pseudo-replication (e.g. when studying a point-source pollutant). Controls are unlikely to be ideal, and the timing and location of sampling will probably be dictated by accessibility (both temporal and spatial). Finally, because global change factors are inherently correlated with the extent of human infl u-ence on a landscape, global change ‘ treatments ’ will almost always covary in ways that make the identifi cation of driving forces diffi cult - for example, the impacts of temperature on range limits are diffi cult to disentangle from the ongoing infl uence of elevated CO 2 and habitat transformation.

In many cases, the challenges above can be addressed. For one, accidental experiments can often be anticipated. For example, mining companies (and other resource extrac-tion agencies) have to submit detailed management plans in many countries, allowing scientists to survey processes of interest both before and after the inevitable disturbance (Laurance et al. 2002, Wu et al. 2003, Bernhardt and Palmer 2011). Th anks to monitoring eff orts by countless conserva-tion agencies and citizen scientists (e.g. IUCN, the Christmas Bird Count), the impending invasion of introduced species as well as the decline of certain species or functional groups can frequently be predicted in advance (Colon-Gaud et al. 2009, Dorcas et al. 2012). Conservation and restoration eff orts, often years in planning, can themselves provide criti-cal opportunities for insight (Hobbs et al. 2006, Schulte et al. 2009, Araiza et al. 2012). Where advance notice is impossible, long-term monitoring eff orts, historical data sets, museum specimens and citizen science can provide information on ‘ pre-treatment ’ conditions (LaDeau et al. 2007, Moritz et al. 2008,

evolutionary dynamics following these large disturbances. Similarly, with a few exceptions we are not aware of studies that have used the ongoing decline of amphibians to docu-ment their role in aquatic foodwebs or ecosystems (Box 2, but see Colon-Gaud et al. 2009, 2010). Being aware of the environmental pressures facing particular study organisms or systems, through scientifi c literature, conferences, and dialogue between natural resource managers and academic scientists, could allow ecologists and evolutionary biologists to better identify the unique opportunities embedded in ongoing global change.

In fact, we were surprised by the low fl ow of informa-tion between traditionally basic versus applied journals in both fi elds (Fig. 1C), especially in the fi eld of evolutionary biology. Has this resulted in a lower number of fundamental insights gained from studying global change in evolution-ary biology relative to ecology? Th is is a diffi cult question to answer, but it does seem to us that it might have – we had a much harder time fi nding examples of evolutionary acci-dental experiments in our literature searches for most global change factors (introduced species being the exception, Strauss et al. 2006a, Callaway and Maron 2006, Sax et al. 2007). Th is is a subjective conclusion, and it is of course possible that the search terms we used to indicate studies of global change are less used by evolutionary biologists in titles and abstracts (Supplementary material Appendix A1, A2). Alternatively, perhaps evolutionary changes in response to the global change factors in question really are rarer than eco-logical responses, infl uencing citation patterns. Regardless of the ultimate reason for these patterns, we believe ‘ accidental experiments ’ provides a useful and underused framework for integrating applied and basic research in both ecology and evolutionary biology.

Consider the advantages and disadvantages of ‘ accidental experiments ’ , and seek them out when desired treatments would be diffi cult or unethical to impose When might accidental experiments better provide us fun-damental insights than traditional approaches, like observa-tional monitoring and manipulative experiments? Th is will depend on the costs (disadvantages) and benefi ts (advantages) of all potential approaches relative to each other (Table 2), as well as the specifi c question being asked. For example, understanding whether a terrestrial grassland community is more limited by the top – down eff ects of herbivores or the bottom up eff ects of soil nutrients is probably more easily ascertained from a manipulative experiment than a landscape scale survey of productivity relative to the density of herbi-vores and nutrient deposition, because treatments in such a manipulative experiment are straightforward to apply (fences, fertizer; Gruner et al. 2008), while herbivore density and nutri-ent deposition regimes across landscapes are potentially con-founded with many other (anthropogenic) variables. In many cases, pairing accidental experiments with manipulative exper-imental studies (Pateman et al. 2012) can allow for stronger inference while incorporating the larger spatio-temporal scale and complexity that accidental experiments allow (a similar argument for pairing observational monitoring and manipu-lative experiments is present in Hewitt et al. 2007).

Most useful is when ongoing global change provides opportunities to study numerous contemporary ecological

1658

Balanya, J. et al. 2006. Global genetic change tracks global climate warming in Drosophila subobscura . – Science 313: 1773 – 1775.

Bard, G. E. 1952. Secondary succession on the Piedmont of New-Jersey. – Ecol. Monogr. 22: 195 – 215.

Bartomeus, I. et al. 2011. Climate-associated phenological advances in bee pollinators and bee-pollinated plants. – Proc. Natl Acad. Sci. USA 108: 20645 – 20649.

Bazzaz, F. A. 1968. Succession on abondoned fi elds in Shawnee Hills southern Illinois. – Ecology 49: 924 – 936.

Beckage, B. et al. 2008. A rapid upward shift of a forest ecotone during 40 years of warming in the Green Mountains of Ver-mont. – Proc. Natl Acad. Sci. USA 105: 4197 – 4202.

Bernhardt, E. S. and Palmer, M. A. 2011. Th e environmental costs of mountaintop mining valley fi ll operations for aquatic eco-systems of the central Appalachians. – Year Ecol. Conserv. Biol. 1223: 39 – 57.

Bierregaard, R. O. et al. 1992. Th e biological dynamics of tropical rain-forest fragments. – Bioscience 42: 859 – 866.

Both, C. and Visser, M. 2001. Adjustment to climate change is constrained by arrival date in a long-distance migrant bird. – Nature 411: 296 – 298.

Both, C. et al. 2009. Climate change and unequal phenological changes across four trophic levels: constraints or adaptations? – J. Anim. Ecol. 78: 73 – 83.

Bradshaw, W. and Holzapfel, C. 2001. Genetic shift in photoperi-odic response correlated with global warming. – Proc. Natl Acad. Sci. USA 98: 14509 – 14511.

Brede, N. et al. 2009. Th e impact of human-made ecological changes on the genetic architecture of Daphnia species. – Proc. Natl Acad. Sci. USA 106: 4758 – 4763.

Bush, G. 1969. Sympatric host race formation and speciation in frugivorous fl ies of genus Rhagoletis (Diptera, Tephritidae). – Evolution 23: 237 – 251.

Buza, L. et al. 2000. Genetic erosion, inbreeding and reduced fi t-ness in fragmented populations of the endangered tetraploid pea Swainsona recta . – Biol. Conserv. 93: 177 – 186.

Callaway, R. M. and Maron, J. L. 2006. What have exotic plant invasions taught us over the past 20 years? – Trends Ecol. Evol. 21: 369 – 374.

Callaway, R. M. et al. 2011. Eff ects of soil biota from diff erent ranges on Robinia invasion: acquiring mutualists and escaping pathogens. – Ecology 92: 1027 – 1035.

Camplani, A. et al. 1999. Carotenoids, sexual signals and immune function in barn swallows from Chernobyl. – Proc. R. Soc. B 266: 1111 – 1116.

Candolin, U. et al. 2007. Changed environmental conditions weaken sexual selection in sticklebacks. – J. Evol. Biol. 20: 233 – 239.

Cannone, N. et al. 2008. Accelerating climate change impacts on alpine glacier forefi eld ecosystems in the European Alps. – Ecol. Appl. 18: 637 – 648.

Carpenter, S. and Brock, W. 2006. Rising variance: a leading indi-cator of ecological transition. – Ecol. Lett. 9: 308 – 315.

Carroll, S. P. et al. 2005. And the beak shall inherit – evolution in response to invasion. – Ecol. Lett. 8: 944 – 951.

Carroll, S. P. et al. 2007. Evolution on ecological time-scales. – Funct. Ecol. 21: 387 – 393.

Cavender-Bares, J. et al. 2009. Th e merging of community ecology and phylogenetic biology. – Ecol. Lett. 12: 693 – 715.

Charmantier, A. et al. 2008. Adaptive phenotypic plasticity in response to climate change in a wild bird population. – Science 320: 800 – 803.

Chen, I. et al. 2009. Elevation increases in moth assemblages over 42 years on a tropical mountain. – Proc. Natl Acad. Sci. USA 106: 1479 – 1483.

Chen, I. et al. 2011. Rapid range shifts of species associated with high levels of climate warming. – Science 333: 1024 – 1026.

Dietl and Flessa 2011, Pateman et al. 2012) . Small numbers of replicates and multivariate environmental stressors, while undesirable, are already familiar to ecologists and evolution-ary biologists studying unique events and increasingly better accommodated by more sophisticated statistical approaches (Clark 2005).

Conclusions

Our infl uence on the planet continues to grow, increas-ingly blurring the boundary between ‘ natural ’ and ‘ human-dominated ’ environments (Hobbs et al. 2006, Marris 2009). We believe that the accidental experiments imposed by these intentional and unintentional human activities have and will continue to provide unique opportunities to understand ecological and evolutionary dynamics (Fukami and Wardle 2005, Sax et al. 2007). We want to be clear that we do not revel in the massive and often negative impacts of human activities, nor do we discount the importance and value of studies documenting global change or outlining valuable approaches to manage or mitigate their negative consequences. Instead, we view accidental experiments as complementary to the observational studies and manipu-lative experiments ecologists and evolutionary biologists often rely on for fundamental insight. We fi rmly believe that accidental experiments will also provide guidance to management; for example, conservation eff orts to reintro-duce apex predators to protected areas have been infl uenced by our understanding that they can have strong top – down eff ects on ecosystem function (Estes et al. 2011, Araiza et al. 2012). We therefore believe that viewing inevitable global change as a scientifi c opportunity can aff ord us insights that will ultimately allow us to better manage and predict change on our human-dominated planet.

Acknowledgements – Research was supported by the National Sci-ence Foundation (NSF DEB Career no. DEB-1054012 to JH; NSF GRFP ’ s to AE, BEM, DH, HSR, KRF, KSS and SMW). Any opinion, fi ndings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily refl ect the views of the National Science Foundation.

References

Ackerly, D. D. and Cornwell, W. K. 2007. A trait-based approach to community assembly: partitioning of species trait values into within- and among-community components. – Ecol. Lett. 10: 135 – 145.

Altermatt, F. 2010. Climatic warming increases voltinism in European butterfl ies and moths. – Proc. R. Soc. B 277: 1281 – 1287.

Anderson, C. N. K. et al. 2008. Why fi shing magnifi es fl uctuations in fi sh abundance. – Nature 452: 835 – 839.

Antonovics, J. 2006. Evolution in closely adjacent plant popula-tions X: long-term persistence of prereproductive isolation at a mine boundary. – Heredity 97: 33 – 37.

Araiza, M. et al. 2012. Consensus on criteria for potential areas for wolf reintroduction in Mexico. – Conserv. Biol. 26: 630 – 637.

Baiser, B. et al. 2008. A perfect storm: two ecosystem engineers interact to degrade deciduous forests of New Jersey. – Biol. Invas. 10: 785 – 795.

1659

Filchak, K. et al. 2000. Natural selection and sympatric divergence in the apple maggot Rhagoletis pomonella . – Nature 407: 739 – 742.

Fitter, A. and Fitter, R. 2002. Rapid changes in fl owering time in British plants. – Science 296: 1689 – 1691.

Fitzpatrick, B. M. and Shaff er, H. B. 2007. Hybrid vigor between native and introduced salamanders raises new chal-lenges for conservation. – Proc. Natl Acad. Sci. USA 104: 15793 – 15798.

Fukami, T. and Wardle, D. 2005. Long-term ecological dynamics: reciprocal insights from natural and anthropogenic gradients. – Proc. R. Soc. B 272: 2105 – 2115.

Fukami, T. et al. 2005. Species divergence and trait convergence in experimental plant community assembly. – Ecol. Lett. 8: 1283 – 1290.

Galetti, M. et al. 2013. Functional extinction of birds drive rapid evolutionary changes in seed size. – Science 340: 1086 – 1090.

Gewin, V. 2008. Riders of a modern-day Ark. – PloS Biol. 6: 18 – 21.

Gleeson, S. K. and Tilman, D. 1990. Allocation and the transient dynamics of succession on poor soils. – Ecology 71: 1144 – 1155.

Goulden, M. L. et al. 2011. Patterns of NPP, GPP, respiration, and NEP during boreal forest succession. – Global Change Biol. 17: 855 – 871.

Green, P. T. et al. 2011. Invasional meltdown: Invader-invader mutualism facilitates a secondary invasion. – Ecology 92: 1758 – 1768.

Grinnell, J. 1919. Th e English sparrow has arrived in Death Valley – an experiment in nature. – Am. Nat. 53: 468 – 472.

Gruner, D. S. et al. 2008. A cross-system synthesis of consumer and nutrient resource control on producer biomass. – Ecol. Lett. 11: 740 – 755.

Hairston, N. G. et al. 1960. Community structure, population control and competition. – Am. Nat. 94: 421 – 425.

Hairston, N. et al. 2005. Species-specifi c Daphnia phenotypes: a history of industrial pollution and pelagic ecosystem response. – Ecology 86: 1669 – 1678.

Hanski, I. 1998. Metapopulation dynamics. – Nature 396: 41 – 49. Hanski, I. and Ovaskainen, O. 2000. Th e metapopulation capacity

of a fragmented landscape. – Nature 404: 755 – 758. Harley, C. D. G. 2011. Climate change, keystone predation and

biodiversity loss. – Science 334: 1124 – 1127. Harrington, R. et al. 1999. Climate change and trophic interac-

tions. – Trends Ecol. Evol. 14: 146 – 150. Harsch, M. A. et al. 2009. Are treelines advancing? A global meta-

analysis of treeline response to climate warming. – Ecol. Lett. 12: 1040 – 1049.

Harvell, C. et al. 2002. Ecology – climate warming and disease risks for terrestrial and marine biota. – Science 296: 2158 – 2162.

Hastings, A. et al. 2005. Th e spatial spread of invasions: new devel-opments in theory and evidence. – Ecol. Lett. 8: 91 – 101.

Hawkes, C. et al. 2006. Arbuscular mycorrhizal assemblages in native plant roots change in the presence of invasive exotic grasses. – Plant Soil 281: 369 – 380.

Hendry, A. 2001. Adaptive divergence and the evolution of repro-ductive isolation in the wild: an empirical demonstration using introduced sockeye salmon. – Genetica 112: 515 – 534.

Hewitt, J. E. et al. 2007. Th e eff ect of spatial and temporal het-erogeneity on the design and analysis of empirical studies of scale-dependent systems. – Am. Nat. 169: 398 – 408.

HilleRisLambers, J. et al. 2012. Rethinking community assembly through the lens of coexistence theory. – Annu. Rev. Ecol. Evol. Syst. 43: 227 – 248.

Hobbs, R. et al. 2006. Novel ecosystems: theoretical and manage-ment aspects of the new ecological world order. – Global Ecol. Biogeogr. 15: 1 – 7.

Clark, J. S. 2005. Why environmental scientists are becoming Bayesians. – Ecol. Lett. 8: 2 – 14.

Colon-Gaud, C. et al. 2009. Assessing ecological responses to catastrophic amphibian declines: patterns of macroinverte-brate production and food web structure in upland Panama-nian streams. – Limnol. Oceanogr. 54: 331 – 343.

Colon-Gaud, C. et al. 2010. Stream invertebrate responses to a catastrophic decline in consumer diversity. – J. N. Am. Benthol. Soc. 29: 1185 – 1198.

Coltman, D. et al. 2003. Undesirable evolutionary consequences of trophy hunting. – Nature 426: 655 – 658.

Cotton, P. 2003. Avian migration phenology and global climate change. – Proc. Natl Acad. Sci. USA 100: 12219 – 12222.

Courchamp, F. and Macdonald, D. 2001. Crucial importance of pack size in the African wild dog Lycaon pictus . – Anim. Con-serv. 4: 169 – 174.

Crozier, L. 2004. Warmer winters drive butterfl y range expansion by increasing survivorship. – Ecology 85: 231 – 241.

D’Antonio, C. M. and Vitousek, P. M. 1992. Biological invasions by exotic grasses, the grass fi re cycle and global change. – Annu. Rev. Ecol. Syst. 23: 63 – 87.

Darimont, C. T. et al. 2009. Human predators outpace other agents of trait change in the wild. – Proc. Natl Acad. Sci. USA 106: 952 – 954.

Darwin, C. R. 1859. On the origin of species by means of natural selection. – John Murray.

De Deyn, G. et al. 2003. Soil invertebrate fauna enhances grassland succession and diversity. – Nature 422: 711 – 713.

Desurmont, G. A. et al. 2011. Evolutionary history predicts plant defense against an invasive pest. – Proc. Natl Acad. Sci. USA 108: 7070 – 7074.

Diamond, J. M. 1983. Ecology – laboratory, fi eld and natural experiments. – Nature 304: 586 – 587.

Dietl, G. P. and Flessa, K. W. 2011. Conservation paleobiology: putting the dead to work. – Trends Ecol. Evol. 26: 30 – 37.

Dirzo, R. and Raven, P. 2003. Global state of biodiversity and loss. – Annu. Rev. Environ. Resour. 28: 137 – 167.

Dorcas, M. E. et al. 2012. Severe mammal declines coincide with proliferation of invasive Burmese pythons in Everglades National Park. – Proc. Natl Acad. Sci. USA 109: 2418 – 2422.

Duckworth, R. A. and Badyaev, A. V. 2007. Coupling of dispersal and aggression facilitates the rapid range expansion of a pas-serine bird. – Proc. Natl Acad. Sci. USA 104: 15017 – 15022.

Edgell, T. C. et al. 2009. Experimental evidence for the rapid evo-lution of behavioral canalization in natural populations. – Am. Nat. 174: 434 – 440.

Edmondson, W. 1970. Phosphorus, nitrogen and algae in Lake Washington after diversion of sewage. – Science 169: 690 – 691.

Edwards, M. and Richardson, A. J. 2004. Impact of climate change on marine pelagic phenology and trophic mismatch. – Nature 430: 881 – 884.

Engstrom-Ost, J. and Mattila, J. 2008. Foraging, growth and habitat choice in turbid water: an experimental study with fi sh larvae in the Baltic Sea. – Mar. Ecol. Progr. Ser. 359: 275 – 281.

Eranen, J. K. et al. 2009. Mountain birch under multiple stressors – heavy metal-resistant populations co-resistant to biotic stress but maladapted to abiotic stress. – J. Evol. Biol. 22: 840 – 851.

Estes, J. et al. 1998. Killer whale predation on sea otters linking oceanic and nearshore ecosystems. – Science 282: 473 – 476.

Estes, J. A. et al. 2011. Trophic downgrading of planet Earth. – Science 333: 301 – 306.

Facon, B. et al. 2008. High genetic variance in life-history strategies within invasive populations by way of multiple introductions. – Curr. Biol. 18: 363 – 367.

1660

M ø ller, A. and Mousseau, T. 2006. Biological consequences of Chernobyl: 20 years on. – Trends Ecol. Evol. 21: 200 – 207.

Montesinos, D. et al. 2012. Neo-allopatry and rapid reproductive isolation. – Am. Nat. 180: 529 – 533.

Morgan, J. 1999. Eff ects of population size on seed production and germinability in an endangered, fragmented grassland plant. – Conserv. Biol. 13: 266 – 273.

Moritz, C. et al. 2008. Impact of a century of climate change on small-mammal communities in Yosemite National Park, USA. – Science 322: 261 – 264.

Murdoch, W. et al. 1985. Biological-control in theory and practice. – Am. Nat. 125: 344 – 366.

Myers, R. A. et al. 2007. Cascading eff ects of the loss of apex predatory sharks from a coastal ocean. – Science 315: 1846 – 1850.

O’Dowd, D. et al. 2003. Invasional ‘ meltdown ’ on an oceanic island. – Ecol. Lett. 6: 812 – 817.

Olsen, E. et al. 2004. Maturation trends indicative of rapid evolu-tion preceded the collapse of northern cod. – Nature 428: 932 – 935.

Olsen, E. M. et al. 2009. Nine decades of decreasing phenotypic variability in Atlantic cod. – Ecol. Lett. 12: 622 – 631.

Palumbi, S. 2001. Evolution – humans as the world’s greatest evo-lutionary force. – Science 293: 1786 – 1790.

Parker, J. D. et al. 2006. Opposing eff ects of native and exotic herbivores on plant invasions. – Science 311: 1459 – 1461.

Parmesan, C. 2006. Ecological and evolutionary responses to recent climate change. – Annu. Rev. Ecol. Evol. Syst. 37: 637 – 669.

Parmesan, C. and Yohe, G. 2003. A globally coherent fi ngerprint of climate change impacts across natural systems. – Nature 421: 37 – 42.

Pateman, R. M. et al. 2012. Temperature-dependent alterations in host use drive rapid range expansion in a butterfl y. – Science 336: 1028 – 1030.

Perovich, D. K. and Richter-Menge, J. A. 2009. Loss of sea ice in the Arctic. – Annu. Rev. Mar. Sci. 1: 417 – 441.

Phillips, B. and Shine, R. 2004. Adapting to an invasive species: toxic cane toads induce morphological change in Australian snakes. – Proc. Natl Acad. Sci. USA 101: 17150 – 17155.

Phillips, B. L. et al. 2006. Invasion and the evolution of speed in toads. – Nature 439: 803 – 803.

Philpott, S. M. et al. 2008. Biodiversity loss in Latin American coff ee landscapes: review of the evidence on ants, birds and trees. – Conserv. Biol. 22: 1093 – 1105.

Post, E. and Forchhammer, M. C. 2008. Climate change reduces reproductive success of an Arctic herbivore through trophic mismatch. – Phil. Trans. R. Soc. B 363: 2369 – 2375.

Reale, D. et al. 2003. Genetic and plastic responses of a northern mammal to climate change. – Proc. R. Soc. B 270: 591 – 596.

Reid, W. et al. 2005. Millenium ecosystem assessment: ecosystems and human well-being. Synthesis. – Millennium Ecosystem Assessment Board.

Reinhart, K. and Callaway, R. 2004. Soil biota facilitate exotic Acer invasions in Europe and North America. – Ecol. Appl. 14: 1737 – 1745.

Ricketts, T. et al. 2001. Countryside biogeography of moths in a fragmented landscape: biodiversity in native and agricultural habitats. – Conserv. Biol. 15: 378 – 388.

Ripple, W. J. and Beschta, R. L. 2006. Linking a cougar decline, trophic cascade and catastrophic regime shift in Zion National Park. – Biol. Conserv. 133: 397 – 408.

Ripple, W. et al. 2001. Trophic cascades among wolves, elk and aspen on Yellowstone National Park’s northern range. – Biol. Conserv. 102: 227 – 234.

Rogers, H. et al. 2012. ‘ Natural experiment ’ demonstrates top – -down control of spiders by birds on a landscape level. – PloS ONE 7: e43446.

Hoekstra, J. et al. 2005. Confronting a biome crisis: global dis-parities of habitat loss and protection. – Ecol. Lett. 8: 23 – 29.

Ims, R. A. et al. 2008. Collapsing population cycles. – Trends Ecol. Evol. 23: 79 – 86.

IPCC, Climate Change Synthesis Report 2007. IPCC, Climate Change Synthesis Report, Fourth Assessment Report. Core Writing Team, Pauchari, R. and Reisinger, A. (eds). – IPCC.

Jackson, J. et al. 2001. Historical overfi shing and the recent collapse of coastal ecosystems. – Science 293: 629 – 638.

Johnson, C. N. and VanDerWal, J. 2009. Evidence that dingoes limit abundance of a mesopredator in eastern Australian for-ests. – J. Appl. Ecol. 46: 641 – 646.

Jump, A. S. and Penuelas, J. 2006. Genetic eff ects of chronic hab-itat fragmentation in a wind-pollinated tree. – Proc. Natl Acad. Sci. USA 103: 8096 – 8100.

Kauserud, H. et al. 2008. Mushroom fruiting and climate change. – Proc. Natl Acad. Sci. USA 105: 3811 – 3814.

Kettlewell, H. 1955. Recognition of appropriate backgrounds by the pale and black phases of Lepidoptera. – Nature 175: 943 – 944.

Kimbro, D. L. et al. 2009. Invasive species cause large-scale loss of native California oyster habitat by disrupting trophic cascades. – Oecologia 160: 563 – 575.

Kolbe, J. et al. 2004. Genetic variation increases during biological invasion by a Cuban lizard. – Nature 431: 177 – 181.

Kurle, C. M. et al. 2008. Introduced rats indirectly change marine rocky intertidal communities from algae- to invertebrate-dominated. – Proc. Natl Acad. Sci. USA 105: 3800 – 3804.

LaDeau, S. L. et al. 2007. West Nile virus emergence and large-scale declines of North American bird populations. – Nature 447: 710 – 713.

Lane, J. E. et al. 2012. Delayed phenology and reduced fi tness associated with climate change in a wild hibernator. – Nature 489: 554 – 557.

Laurance, W. F. 2008. Th eory meets reality in fragmented forests. – Anim. Conserv. 11: 364 – 365.

Laurance, W. et al. 2002. Ecosystem decay of Amazonian forest fragments: a 22-year investigation. – Conserv. Biol. 16: 605 – 618.

Lavergne, S. and Molofsky, J. 2007. Increased genetic variation and evolutionary potential drive the success of an invasive grass. – Proc. Natl Acad. Sci. USA 104: 3883 – 3888.

Lenoir, J. et al. 2008. A signifi cant upward shift in plant species optimum elevation during the 20th century. – Science 320: 1768 – 1771.

Leopold, A. et al. 1947. A survey of over-populated deer ranges in the United States. – J. Wildlife Manage. 11: 162 – 177.

Levine, J. and D’Antonio, C. 2003. Forecasting biological inva-sions with increasing international trade. – Conserv. Biol. 17: 322 – 326.

Lubchenco, J. et al. 2012. Science in support of the deepwater hori-zon response. – Proc. Natl Acad. Sci. USA 109: 20212 – 20221.

MacArthur, R. H. 1972. Geographical ecology; patterns in the distribution of species. – Harper and Row.

Madsen, T. et al. 1996. Inbreeding depression in an isolated popu-lation of adders Vipera berus . – Biol. Conserv. 75: 113 – 118.

Marris, E. 2009. Ecology: ragamuffi n Earth. – Nature 460: 450 – 453.

Martinez, J. L. 2009. Th e role of natural environments in the evo-lution of resistance traits in pathogenic bacteria. – Proc. R. Soc. B 276: 2521 – 2530.

May, R. 1977. Th resholds and breakpoints in ecosystems with a multiplicity of stable states. – Nature 269: 471 – 477.

Miller-Rushing, A. J. and Primack, R. B. 2008. Global warming and fl owering times in Th oreau’s concord: a community per-spective. – Ecology 89: 332 – 341.

Mitchell, C. E. and Power, A. G. 2003. Release of invasive plants from fungal and viral pathogens. – Nature 421: 625 – 627.

1661

Templeton, A. et al. 2001. Disrupting evolutionary processes: the eff ect of habitat fragmentation on collared lizards in the Mis-souri Ozarks. – Proc. Natl Acad. Sci. USA 98: 5426 – 5432.

Terborgh, J. et al. 2001. Ecological meltdown in predator-free for-est fragments. – Science 294: 1923 – 1926.

Th ackeray, S. J. et al. 2010. Trophic level asynchrony in rates of phenological change for marine, freshwater and terrestrial environments. – Global Change Biol. 16: 3304 – 3313.

Tilman, D. et al. 2001. Forecasting agriculturally driven global environmental change. – Science 292: 281 – 284.

Tingley, M. W. et al. 2012. Th e push and pull of climate change causes heterogeneous shifts in avian elevational ranges. – Global Change Biol. 18: 3279 – 3290.

Torchin, M. et al. 2003. Introduced species and their missing parasites. – Nature 421: 628 – 630.

Vie, J. C. et al. 2009. Wildlife in a changing world – an analysis of the 2008 IUCN red list of threatened species. – � www.iucnredlist.org �

Vila, C. et al. 2003. Rescue of a severely bottlenecked wolf ( Canis lupus ) population by a single immigrant. – Proc. R. Soc. B 270: 91 – 97.

Visser, M. et al. 1998. Warmer springs lead to mistimed reproduction in great tits ( Parus major ). – Proc. R. Soc. B 265: 1867 – 1870.

Vitousek, P. and Walker, L. 1989. Biological invasion by Myrica faya in Hawaii – plant demography, nitrogen-fi xation, ecosystem eff ects. – Ecol. Monogr. 59: 247 – 265.

Vitousek, P. et al. 1997. Human domination of Earth’s ecosystems. – Science 277: 494 – 499.

Vonlanthen, P. et al. 2012. Eutrophication causes speciation reversal in whitefi sh adaptive radiations. – Nature 482: 357 – 362.

Wake, D. B. and Vredenburg, V. T. 2008. Are we in the midst of the sixth mass extinction? A view from the world of amphib-ians. – Proc. Natl Acad. Sci. USA 105: 11466 – 11473.

Ward, J. L. et al. 2012. Discordant introgression in a rapidly expanding hybrid swarm. – Evol. Appl. 5: 380 – 392.

Wassen, M. J. et al. 2005. Endangered plants persist under phos-phorus limitation. – Nature 437: 547 – 550.

Westemeier, R. et al. 1998. Tracking the long-term decline and recov-ery of an isolated population. – Science 282: 1695 – 1698.

Whitham, T. G. et al. 2006. A framework for community and ecosystem genetics: from genes to ecosystems. – Nat. Rev. Genet. 7: 510 – 523.

Williams, J. W. and Jackson, S. T. 2007. Novel climates, no-analog communities, and ecological surprises. – Front. Ecol. Environ. 5: 475 – 482.

Willis, C. G. et al. 2008. Phylogenetic patterns of species loss in Th oreau’s woods are driven by climate change. – Proc. Natl Acad. Sci. USA 105: 17029 – 17033.

Winder, M. and Schindler, D. 2004. Climate change uncouples trophic interactions in an aquatic ecosystem. – Ecology 85: 2100 – 2106.

Wu, J. et al. 2003. Th ree-Gorges dam – experiment in habitat frag-mentation? – Science 300: 1239 – 1240.

Yoshida, T. et al. 2003. Rapid evolution drives ecological dynamics in a predator – prey system. – Nature 424: 303 – 306.

Zangerl, A. R. and Berenbaum, M. R. 2005. Increase in toxicity of an invasive weed after reassociation with its coevolved herbivore. – Proc. Natl Acad. Sci. USA 102: 15529 – 15532.

Roman, J. 2006. Diluting the founder eff ect: cryptic invasions expand a marine invader’s range. – Proc. R. Soc. B 273: 2453 – 2459.

Roman, J. and Darling, J. A. 2007. Paradox lost: genetic diversity and the success of aquatic invasions. – Trends Ecol. Evol. 22: 454 – 464.

Rudge, D. 2005. Th e beauty of Kettlewell’s classic experimental demonstration of natural selection. – Bioscience 55: 369 – 375.

Ryther, J. and Dunstan, W. 1971. Nitrogen, phosphorus, and eutrophication in the coastal marine environment. – Science 171: 1008 – 1013.

Saccheri, I. et al. 1998. Inbreeding and extinction in a butterfl y metapopulation. – Nature 392: 491 – 494.

Saccheri, I. J. et al. 2008. Selection and gene fl ow on a diminishing cline of melanic peppered moths. – Proc. Natl Acad. Sci. USA 105: 16212 – 16217.

Sala, O. et al. 2000. Biodiversity – global biodiversity scenarios for the year 2100. – Science 287: 1770 – 1774.

Salmon, A. et al. 2005. Genetic and epigenetic consequences of recent hybridization and polyploidy in Spartina (Poaceae). – Mol. Ecol. 14: 1163 – 1175.

Sasaki, K. et al. 2009. Rapid evolution in the wild: changes in body size, life-history traits and behavior in hunted popula-tions of the Japanese Mamushi snake. – Conserv. Biol. 23: 93 – 102.

Sax, D. F. et al. 2007. Ecological and evolutionary insights from species invasions. – Trends Ecol. Evol. 22: 465 – 471.

Scheff er, M. et al. 1993. Alternative equilibria in shallow lakes. – Trends Ecol. Evol. 8: 275 – 279.

Schulte, D. M. et al. 2009. Unprecedented restoration of a native oyster metapopulation. – Science 325: 1124 – 1128.

Seehausen, O. et al. 1997. Cichlid fi sh diversity threatened by eutrophication that curbs sexual selection. – Science 277: 1808 – 1811.

Siemann, E. et al. 2006. Rapid adaptation of insect herbivores to an invasive plant. – Proc. R. Soc. B 273: 2763 – 2769.

Smith, S. et al. 2004. Cross-cordillera exchange mediated by the Panama Canal increased the species richness of local freshwater fi sh assemblages. – Proc. R. Soc. B 271: 1889 – 1896.

Smith, V. H. et al. 2006. Eutrophication of freshwater and marine ecosystems. – Limnol. Oceanogr. 51: 351 – 355.

Stevens, C. J. et al. 2004. Impact of nitrogen deposition on the species richness of grasslands. – Science 303: 1876 – 1879.

Stinson, K. A. et al. 2006. Invasive plant suppresses the growth of native tree seedlings by disrupting belowground mutualisms. – PloS Biol. 4: 727 – 731.

Stoker, C. et al. 2003. Sex reversal eff ects on Caiman latirostris exposed to environmentally relevant doses of the xenoestrogen bisphenol A. – Gen. Comp. Endocrinol. 133: 287 – 296.

Strauss, S. Y. et al. 2006a. Exotic taxa less related to native species are more invasive. – Proc. Natl Acad. Sci. USA 103: 5841 – 5845.

Strauss, S. Y. et al. 2006b. Evolutionary responses of natives to introduced species: what do introductions tell us about natural communities? – Ecol. Lett. 9: 354 – 371.

Suding, K. N. et al. 2005. Functional- and abundance-based mech-anisms explain diversity loss due to N fertilization. – Proc. Natl Acad. Sci. USA 102: 4387 – 4392.

Supplementary material (available online as Appendix oik-00698 at � www.oikosoffi celu.se/appendix � ). Appen-dix A1 and A2.